Stopped object filtering for side object detection system

ABSTRACT

An object-presence alert is given to a driver by a vehicular side-object detection system in response to a remote sensor for sensing objects in a predetermined zone of interest along side a vehicle. The zone of interest includes a front region and a rear region, and the remote sensor provides sensor data to generate a set of localized detection points. When detection points are sensed in the zone of interest, then a plurality of respective sets of detection points are collected at successive sample times. For each of the sets of detection points, a tracking type of the object within the zone of interest is determined in comparison to a speed of the vehicle and the object is classified as either a moving vehicle or a stationary object in response to the tracking type and in response to locations of the detection points in the zone of interest. If the object first appeared in other than the front region, then a short observation period is selecting including a first predetermined number of sets of detection points and otherwise a long detection period is selected including a second predetermined number of sets of detection points longer than the first predetermined number. A number of times that the object is classified as a moving vehicle within the selected observation period is compared to a predetermined percentage threshold and the alert is initiated if classified as a moving vehicle for greater than the predetermined percentage threshold.

CROSS REFERENCE TO RELATED APPLICATIONS

[0001] This application is related to co-pending U.S. application Ser.No. (V203-0176) entitled “System and Method for Determining ObjectLocation from Side-Looking Sensor Data,” and U.S. application Ser. No.(V203-0199) entitled “Method for Determining Object Classification fromSide-Looking Sensor Data,” both filed concurrently herewith andincorporated herein by reference in their entirety.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH

[0002] Not Applicable.

BACKGROUND OF THE INVENTION

[0003] The present invention relates in general to side object detectionsystems for motor vehicles, and, more specifically, to distinguishingbetween stationary and moving objects within a detection zone.

[0004] Automotive systems known as side object detection systems (SODS)utilize “side-looking” remote sensors for such applications asblind-spot detection and lane change aid. These applications aredesigned to alert the driver to potential hazards, e.g., objects thatmay be located adjacent to the host vehicle. The remote sensors mayemploy radar transceivers, light sensors, ultrasonic sensors, and othertechnologies.

[0005] One objective of the side-looking sensors is to identify thepresence and location of objects within a predetermined zone of interestadjacent to the vehicle. Radar sensors detect and locate objects bytransmitting electromagnetic energy which reflects off of objects withinthe sensor field-of-view. The reflected signal returns to the radarsensor where it is processed to determine the round-trip travel time ofthe transmitted/received energy. The round trip travel time is directlyproportional to the range of the target from the radar sensor. Inaddition to range determination, there are methods to determine azimuth(i.e. cross-range) location of detected objects such as multiplescanned/switched beams and mono-pulse implementations. Therefore,depending upon its complexity, the radar is capable of locating objectsin both range and azimuth relative to the sensor location.

[0006] Based on the location of detected objects, an automatic systemmust decide whether a detection is one for which it should alert thedriver. Under certain conditions, it may be undesirable to alwaysgenerate an alert every time that any object is detected in thedetection zone. For example, side-looking radar sensors will besubjected to reflections from common roadway structures such asguard-rails and roadside signs. These objects may not constitute athreat to which the driver desires to be alerted since they arestationary.

[0007] Radar sensors are capable of providing accurate rangemeasurements to objects located within the sensors' field-of-view. Insome cases, the sensor may also provide range rate (via Doppler) andazimuth (cross-range) information about the objects. However, due to thecomplexity of the driving environment, it has not been possible for aradar sensor to discriminate between the various driving scenarioswithout extensive processing and expensive sensor designs. It would bedesirable to discriminate between objects for which an alert should orshould not be provided using relatively simple sensors and withoutexcessive computational resources.

SUMMARY OF THE INVENTION

[0008] This invention describes methods for enhancing side-looking radarsensor design and signal processing to identify and discriminate betweena variety of driving scenarios. With the driving scenario properlyidentified, higher level system decisions (e.g., whether to alert adriver or activate a restraint mechanism) can be properly made.

[0009] In one aspect of the invention, a method is provided forcontrolling an object-presence alert in a vehicular side-objectdetection system in response to a remote sensor for sensing objects in apredetermined zone of interest along side a vehicle. The zone ofinterest includes a front region and a rear region, and the remotesensor provides sensor data to generate a set of localized detectionpoints. When detection points are sensed in the zone of interest, then aplurality of respective sets of detection points are collected atsuccessive sample times. For each of the sets of detection points, atracking type of the object within the zone of interest is determined incomparison to a speed of the vehicle and the object is classified aseither a moving vehicle or a stationary object in response to thetracking type and in response to locations of the detection points inthe zone of interest. If the object first appeared in other than thefront region, then a short observation period is selecting including afirst predetermined number of sets of detection points and otherwise along detection period is selected including a second predeterminednumber of sets of detection points longer than the first predeterminednumber. A number of times that the object is classified as a movingvehicle within the selected observation period is compared to apredetermined percentage threshold and the alert is initiated ifclassified as a moving vehicle for greater than the predeterminedpercentage threshold.

BRIEF DESCRIPTION OF THE DRAWINGS

[0010]FIG. 1 is an overhead view showing a side-object detection zone ofinterest and a remote sensor field of view.

[0011]FIG. 2 shows coordinate systems for specifying locations within afield of view.

[0012]FIG. 3 illustrates monopulse radar transmission beams covering afield of view.

[0013]FIG. 4 illustrates a scanning/multiple switched beam radartransmission covering the field of view.

[0014]FIG. 5 is a graphic depiction showing various driving scenarioswherein objects are detected by a side-object detection system.

[0015]FIG. 6 is a flowchart showing an overall and decision tree fordetermining whether to generate an alert to the driver of a vehicle.

[0016]FIG. 7 as a flowchart showing a preferred embodiment of thepresent invention.

[0017]FIG. 8 is a flowchart showing a method for processing a miss ingreater detail.

[0018]FIG. 9 is a flowchart showing a method for processing a hit ingreater detail.

[0019]FIG. 10 is a flowchart showing a method for determining an entrytype.

[0020]FIG. 11 shows front, side, and rear regions within a zone ofinterest.

[0021]FIG. 12 is a flowchart showing a method for determining a locationtype.

[0022]FIG. 13 is a flowchart showing a method for determining a tracktype.

[0023]FIG. 14 is a flowchart showing a method for determining aclassification type.

[0024]FIGS. 15a and 15 b are a flowchart showing a preferred embodimentof the alert processing of the present invention.

[0025]FIG. 16 is a block diagram showing a remote sensing systemaccording to the present invention.

DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS

[0026] Referring to FIG. 1, a remote sensor 10 is mounted towards therear of a vehicle 11 and is pointed generally in a directionperpendicular to the vehicle's direction of travel (i.e., the sensor isside-looking). By measuring range and bearing (or azimuth) to detectedtargets (i.e., sensed detection points) the side obstacle detectionsystem can determine if an object is located within a zone of interest12, also known as a detection zone. Sensor 10 typically has an actualfield of view 13 which may encompass areas beyond zone of interest 12.Although a zone of interest is shown on only one side of vehicle 11, atypical side object detection system includes sensors deployed on boththe left and right sides of a vehicle in order to cover blind spots onboth sides of vehicle 11.

[0027] Sensor 10 may be comprised of a radar sensor, for example, and iscapable of supplying at least two types of information: 1) range todetected targets, and 2) bearing (i.e., azimuth angle) to detectedtargets. As an added piece of information, the measurement of relativerange rate via Doppler frequency shift can be utilized. The use ofDoppler measurements has been used to identifying stopped objects usinga radar sensor, however, it is of limited value in a side-looking casesince the radar's field of view is generally perpendicular to thevehicle's direction of travel and any Doppler shift is minimal forobjects in the zone of interest.

[0028] As shown in FIG. 2, when a detection point or target 15 is sensedwithin the sensor's field of view 13, a range 16 from sensor 10 and anazimuth angle 17 from a reference direction 18 (e.g., perpendicular fromthe side of vehicle 11) are determined using methods well known in theart in accordance with the type of remote sensor being employed. In apreferred embodiment of the invention, the coordinates of detectionpoints are converted into X/Y Cartesian coordinates with the x dimensioncorresponding to perpendicular distance from a corresponding side of thevehicle and with the y dimension corresponding to parallel distance froma reference point, such as the position of the remote sensor.

[0029] In a preferred embodiment, targets are detected and localizedusing monopulse radar. An example beam pattern is shown in FIG. 3. Asingle-lobed radar pulse is transmitted and received alternately with atwo-lobed radar pulse 21. As is known in the art, by comparing thereflection time (i.e., range) of target detections with the relativeamplitudes of target detections at the same range, individual detectionpoints can be located.

[0030] In an alternative embodiment shown in FIG. 4, a multiple beamradar sensor generates separate detection beams 22 directed atrespective slices within field of view 13. A narrow radar beam or otherbeams such as a laser beam can also be electronically scanned across thefield of view so that the beam direction at the time of detectiondirectly gives the azimuth angle.

[0031] When a sufficient number of detection points have been sensed,the presence of an object in the zone of interest can be reliablydetermined. In some conditions, however, it is not usually desirable toinitiate an alert (e.g., lighting a warning light or sounding an alarm)for every possible type of object that may be detected. In particular,stationary objects approach the vehicle from a forward direction withinthe driver's vision and no warning may be necessary or desired.

[0032] In general, there are two types of stationary objects that mayenter the zone of interest: 1) those which are relatively short andspread over a small azimuth angle, such as sign posts, poles, and bridgepillars, and 2) those which have relatively wide longitudinal extent,such as concrete medians, guardrails, continuous roadside “clutter” suchas groups of trees or berms. A challenge not satisfactorily met by theprior art is the need to distinguish stationary objects from movingvehicles in the zone of interest.

[0033] Various driving scenarios are shown in FIG. 5. In Case 1, vehicle11 is overtaken by a faster moving vehicle 25. Thus, at a time t₁,vehicle 25 is approaching the rear edge of zone of interest 12. At atime t₂, vehicle 25 has entered zone 12 and is detected as an objectwithin zone 12. By a time t₃, vehicle 25 has emerged from the front edgeof zone 12 and is visible to the driver of vehicle 11. During the timesthat vehicle 25 is within zone 12, it is desirable to generate an alertnotification or warning to the driver of vehicle 11.

[0034] In Case 2, vehicle 11 overtakes a slower moving vehicle 26. Attime t₁, vehicle 26 is forward of vehicle 11 and can be seen by itsdriver. At time t₂, vehicle 26 is present in zone 12 but should notraise an alert if it is quickly overtaken, i.e., not present in a blindspot for more than a brief period of time. At time t₃, vehicle 26 hasemerged from zone 12 so that no alert is to be produced.

[0035] A scenario involving a stationary object is shown in Case 3wherein vehicle 11 passes a pole 27 situated off of the road surface.Pole 27 passes or tracks through zone 12 even more quickly than vehicle26 since pole 27 has no forward motion. Since pole 27 does notconstitute a hazard to vehicle 11, no alert should be initiated when itis present within zone 12.

[0036] Case 4 shows another scenario wherein a stationary object iscomprised of a long structure such as a guardrail, a fence, or a roadwaymedian. Vehicle 11 approaches a guardrail 28 at time t₁ and travelsalongside guardrail 28 for a long distance as at time t₂. Eventually,vehicle 11 clears guardrail 28 at time t₃. No alert should be initiatedfor any such long, stationary structure.

[0037] Since the surfaces of any sensed objects may be irregular and canprovide inconsistent return signals (e.g., the strength of radarreflections from a point on an object can be very sensitive to the angleof the incident radar waves), the sensed detection points in each of theforegoing scenarios are inherently noisy thereby making it difficult todistinguish one type of object from another. Specialized, high costsensors and/or complex, resource intensive computer processing havepreviously been needed for classifying objects using remote sensor data.The present invention overcomes these difficulties using inexpensivesensors and processing together with an improved decision methodology asshown in FIG. 6 for filtering out stationary objects so that analert/warning is not initiated unless an object is reliably classifiedas a moving vehicle.

[0038] A preferred decision tree of the present invention shown in FIG.6 includes a plurality of decision levels 30 through 33 for providing analert when another vehicle may be moving within a zone of interest(e.g., blind spot) of a vehicle but suppressing an alert for any othertypes of (e.g., stationary) objects. The method of FIG. 6 begins with acheck in step 34 to determine whether any object is detected within thezone of interest. Once an object has been detected, a host status level30 is carried out wherein a check is made in step 35 to determinewhether the host vehicle is in motion (e.g., is traveling with a speedover a speed threshold). If the vehicle is not in motion or moving at aspeed less than the speed threshold, then an alert is produced if anyobject is detected in the zone of interest. For instance, when a vehicleis parking or just beginning to move, it may be desirable to be alertedwhen any objects are present. As shown in box 30, a discriminator forthe host status level could be vehicle speed information obtained from avehicle multiplex bus communication with a powertrain control module,for example. In an alternative embodiment, it may be determined by avehicle manufacturer or driver that no alerts should be given when notin motion. In that case, host status level 30 and step 35 may beskipped.

[0039] Once a host vehicle is in motion, further levels of the decisiontree are utilized. In entry level 31, a check is made in step 36 todetermine whether an object entered the zone of interest from the rearor from the side of the zone (i.e., from other than the front of thezone, such that the object is very likely a moving vehicle and may nothave already been seen by the driver). If entry is into the zone is intothe rear or side regions of the zone then an alert is initiated. Apreferred discriminator for entry level 31 is the Y-coordinate alone toidentify entry into a rear region or the X/Y-coordinates to identify aside region entry. When a vehicle is making a sharp turn, it issometimes possible that a stationary object first enters the side orrear regions of the zone of interest. Thus, an alternate embodiment isprovided below wherein the entry region controls the length of anobservation period during which an object is classified as a vehicle ora stationary object and wherein a short observation window and a testmore slanted toward classifying the object as a vehicle are employedwhen the object first entered the side or rear regions of the zone ofinterest.

[0040] In a more simplified alternative embodiment, the entry levelcould be used alone such that 1) an alert is initiated whenever anobject enters from the side or rear, and 2) a decision is made not toinitiate an alert for an object that enters from the front no matterwhat that object does within the zone of interest after entering.

[0041] In the embodiment of FIG. 6, if an object enters the front regionof the zone (or if it is not possible to determine the region of entry),then the decision tree progresses to a tracking level 32. A check ismade in step 37 to determine whether the object is tracking through thezone of interest as though it is stationary (or moving in the oppositedirection as the host vehicle). If tracking through the zone, then noalert is initiated for the object. Discriminators useful for trackinglevel 32 include Y-coordinate flow analysis such as trend of Y_(max),Y_(min), Y_(mean), or X.

[0042] If the object does not track through (i.e., remains in) the zone,then an object classification level 33 is entered wherein adetermination is made in step 38 whether or not the object is a vehicle.If the object is classified as a vehicle then an alert is generated,otherwise there is no alert. Discriminators for determining whether thedetection points correspond to a vehicle include range and anglevariance or trends, X and Y variance, cross-correlation of X and Y, Xand Y values over time, signal reflection amplitude averages, amplitudemaximums and minimums, and amplitude variance.

[0043] The present invention may be used in systems employing varioussensing technologies with well known signal processing methods todetermine sets of detection points at respective sample times (e.g.,every 30 milliseconds). The data may be processed using well knowngeneral purpose or customized microcontrollers, for example.

[0044] A detailed method for implementation in a controller that isinterfaced with a remote sensor module is shown in FIG. 7. Thisembodiment preferably employs the variable observation period mentionedabove. In step 40, a set of detection points at the current sample timeare obtained from the remote (e.g., radar) sensor. Since sensor data istypically created in the form of range and azimuth data, the set ofdetection points is preferably converted to X/Y coordinates in step 41to simplify some of the subsequent processing. However, conversion toX/Y coordinates is optional since each type of processing canequivalently be conducted using azimuth and range (i.e., polar)coordinates.

[0045] A check is made in step 42 to determine whether any detectionpoints have been sensed that are within the zone of interest. If yes,then the point(s) are processed as a hit in step 43; otherwise, they areprocessed as a miss in step 44. In step 45, an entry type is determined.A location type is determined in step 46 for assisting in thedetermination of a track type in step 47 and a target classification isdetermined in step 48. Based on the determinations made in steps 45-48,the status of an alert/warning indication is processed in step 49 andthen a return is made to get the next set of detection points in step40.

[0046] The processing of a miss in step 44 is shown in greater detail inFIG. 8. Due to the random fluctuations of target detections betweensample times, the present invention provides for processing of hits andmisses so that detections over several consecutive sample times canoptionally be considered together. In addition, the presence of targetdetections within the sensor field-of-view but outside of the actualzone of interest (e.g., greater than one road lane away from the hostvehicle) is monitored so that information about an object gathered priorto its crossing into the zone of interest can be utilized.

[0047] In step 50, a check is made to determine whether the detectionpoint nearest the remote sensor (i.e., with the smallest range) iswithin a predetermined buffer area around the zone of interest (i.e.,since this is a miss, it cannot be within the zone of interest). Thebuffer zone is used to track objects just outside the zone of interestso that the necessity of initiating an alert can be detected morequickly if and when the object enters the zone of interest. If in thebuffer zone, then a check is made in step 51 to determine whether acounter ConsecHits is less than a predetermined number of required hitsReqHits minus 1 in step 51. If yes, then the current value of ConsecHitsis incremented by one in step 52. Otherwise, the value of ConsecHits isunchanged. Thus, if ConsecHits is already equal to the required numberof hits ReqHits and a detected object moves out from the zone ofinterest into the buffer zone, the value of ConsecHits remains at thelevel of ReqHits. If the object thereafter re-enters the zone ofinterest, an alert can be initiated more quickly.

[0048] If the nearest detection point was found not to be within thebuffer zone in step 50, then the value of ConsecHits is reset to zero instep 53. After any updating of ConsecHits in steps 52 or 53, a check ismade in step 54 to determine whether a counter ConsecMisses is less thana predetermined number of required misses MissReqd. If not, then anychanges made to the counters are stored in a master record in step 55.Such master record is accessed by each of the routines of FIG. 7 duringtheir operation (i.e., the master record includes detection points for aplurality of consecutive sets as well as track type and class typedeterminations for each set so that these can be retrieved for eachselected observation period). If the value of ConsecMisses is less thanMissReqd, then ConsecMisses is incremented in step 56 before updatingthe record in step 55.

[0049] The processing of a hit (i.e., a set of detection points whereinat least one point falls within the zone of interest) is shown ingreater detail in FIG. 9. The counter ConsecMisses is reset to zero instep 57. Then a check is made in step 58 to determine whether ConsecHitsis less than HitsReqd. If yes, then ConsecHits is incremented in step 59and the record for the current sample time is updated in step 60. IfConsecHits has already reached HitsReqd, then the record is updated instep 60 without further incrementing ConsecHits. The predetermined valueof HitsReqd is selected to ensure that an object is really present andit is not just noisy sensor data. HitsReqd may have a value of about 4,for example. Similarly, the predetermined value of MissReqd ensures thatan object has really departed and may also have a value of about 4, forexample.

[0050] The determination of an entry type is shown in FIG. 10. A checkis made in step 61 whether an entry type is already known. If so, thenthe entry type continues to be the original entry type in step 62 andany record updating is performed in step 63. In other words, once anentry type is determined for an object, the entry type does not changeas long as an object continues to be present.

[0051] Step 64 checks to determine whether enough sets of detectionpoints are available to make a determination of entry type. Preferablytwo samples should be available, although the present invention alsocontemplates making a determination with only one sample. If not enoughsamples are available in the master record, then entry type is set tounknown and the process exits at step 63.

[0052] If enough samples are present, then a check is made in step 66 todetermine whether any fixed detection points are in the zone ofinterest. This step may be necessitated according to the type of remotesensor being used. With a monopulse radar, for example, it may bepossible to have detection points with a known range but without aresolvable azimuth angle. Therefore, if the only available detectionpoints cannot be fixed within the zone, then entry type is set tounknown in step 65. Otherwise, step 67 checks to determine whether allthe Y_(max) values (i.e., each respective Y_(max) value from eachrespective sample set) are less than a rear/front (R/F) threshold. Thus,if all the farthest forward detection points is each sample set underconsideration is rearward of the R/F threshold then the entry type isset to Rear in step 68.

[0053]FIG. 11 shows zone 12 including a rear region 75, a front region76, and a side region 77 as determined by R/F threshold 78 and afront/side (F/S) threshold 79. In a preferred embodiment, at least theR/F threshold is adjusted in response to the speed of the host vehiclesince the range of front to back positions at which a stationary objectmay be first detected increases as the vehicle speed increases. The Yvalue of the R/F threshold may be determined according to the formula:

Threshold=Limit−(V·0.044704·R·2)

[0054] where limit is a beginning (forward) position of the threshold atlow speed, V is vehicle speed in KPH, the factor 0.044704 converts fromKPH to cm/msec, R is the sensor update rate in msec, and the factor of 2accounts for the possibility that an object was just outside the zone ona previous sample pulse. A lower limit may be provided below which the Yvalue is not allowed to go.

[0055] Returning to FIG. 10, if there was a Y_(max) value forward of theR/F threshold in step 67, then a check is made in step 70 to determinewhether all Y_(min) values are greater than the R/F threshold. If not,then detection points first appeared on both sides of the threshold andthe entry type is set to (or remains) unknown in step 65. Otherwise, theentry must now be distinguished between a front and a side entry (i.e.,front entry objects should already have been seen by the driver but sideentry objects may have come from the driver's blind spot). A check ismade in step 71 to determine whether all X_(min) are greater than theF/S threshold. If so, the entry type is set to Side in step 72;otherwise it is set to Front in step 73.

[0056] The process for determining an object location (described ingreater detail in co-pending application serial number (V203-0176) isshown in FIG. 12. The location type assists in determining an objecttrack type and/or an object classification type as described below. Instep 80, a check is made to determine whether at least one detectionpoint has a fixed location within the zone. If not, then location typeis set to unknown in step 81 and the record is updated in step 85.

[0057] As long as one fixed detection point is present, then theY-coordinate value (Y_(near)) of the detection point nearest in range tothe sensor location (at Y=0) is found in step 82. Generally, objectsmake their closest approach to the remote sensor when they directlyoutward from the sensor (i.e., are intersecting a line perpendicular tothe host vehicle's direction of travel and originating at the sensor).Thus, a check is made in step 83 to determine whether Y_(near) is withina central range centered on Y=0. If within this threshold range, thenthe location type is set to On-center in step 84 and the record isupdated in step 85.

[0058] If Y_(near) is not within the threshold range, then a check ismade in step 86 to determine whether Y_(max) multiplied by Y_(min) isless than zero (i.e., whether there are both positive and negativevalues of Y). If so, then location type is set to Spans in step 87. Ifnot spanning, then step 88 compares any Y value (e.g., Y_(max)) withzero to determine whether the location type is Front (step 89) or Rear(step 90).

[0059] The track decision level is shown in greater detail in FIG. 13.In step 91, a check is made to determine whether at least one detectionpoint has a fixed location within the zone. If not, then track type isset to its previous value in step 92 and the record is updated in step93. As long as one fixed detection point is present, then a check ismade in step 94 to determine whether a location type is known. If not,then track type remains with its previous value.

[0060] If location type is known, then an estimate of the Y-rate of theobject (i.e., relative speed as compared to the host vehicle) isdetermined in step 95. The Y-rate may be estimated by determining theslope of a smoothed Y_(mean) (or Y_(max) or Y_(min)) over a plurality ofsample times (i.e., sets of detection points). In other words, anaverage of all the Y values for a set of detection points at one sampletime is determined. Then a second such average is determined for one ormore subsequent (or previous) sets of detection points. The change in Ydivided by the sample time yields the Y-rate. Since a stationary objectmoves at the same relative speed but in a direction opposite to thevehicle motion, its Y-rate would be negative. Thus, the Y-rate iscompared to a ThruThreshold in step 96 and if less than (i.e., morenegative than) the threshold then the track type is set to Through instep 97. The tracking threshold may preferably be determined accordingto a formula:

ThruThreshold=−V·0.028·R·ToleranceFactor

[0061] wherein the factor of 0.028 converts KPH to cm/msec andToleranceFactor provides an adjustment to control how closely the ratesneed to match.

[0062] It may be desirable to identify other tracks types of Creep Back,Creep Forward, and Stagnant using other thresholds as shown in steps98-102.

[0063] The object classification level is shown in greater detail inFIG. 14. The primary goal is to identify a vehicle moving along with thetarget vehicle, but other classifications such as barrier (e.g.,guardrail or fence), small fixed object (e.g., pole), or clutter (e.g.,interspersed trees, berms, or multiple small objects) can also beidentified.

[0064] A check is made in step 110 to determine whether a sufficientnumber of hits exist to determine a classification. If not, then classtype retains its previous value in step 111 and the record is updated instep 112. If sufficient hits have been detected, then the objectlocation type is checked. Thus, step 113 checks whether the locationtype is On-center. If so, then the object should be either a vehicledirectly alongside the host vehicle or a long structure such as aguardrail since these objects are the only ones likely to create astrong specular radar reflection.

[0065] If location type is On-center, then a check is made in step 114to determine whether the object's size is greater than a size threshold.The size (i.e., two-dimensional area) of the object is preferablydetermined by multiplying the span (i.e, spatial spread) in Y times thespan in X (or other suitable orthogonal directions). For example, thesize may be determined according to the formula:

(Y_(max)−Y_(min))·(X_(max)−X_(min))

[0066] The spans in Y and X may be determined over several sets ofdetection points. If object size is not larger than (i.e., is less than)the size threshold, then the object class is set as Barrier in step 115.Detection points reflected from a barrier, such as a guardrail, willspan over a smaller (e.g., thinner) area than points reflected from avehicle because the reflecting surface of a vehicle is more irregular(e.g., wheel wells, roof panel, glass panels, etc.). Therefore, a largerobject size potentially indicates a vehicle.

[0067] Otherwise, a check is made in step 116 for comparing thestability of the size value over time with a stability threshold. Thestability measure depends on the difference (variance) of the size valuefrom sample time to sample time, so that a higher stability means alower number. If the stability value is above a stability threshold(i.e., the detected size varies a lot from sample to sample), then theobject class is set to Barrier in step 115.

[0068] Otherwise, a check is made in step 117 to determine whether anamplitude of sensed detection points is greater than a threshold. In thecase of radar sensors, the strongest return signals to the sensor couldbe expected to come from flat planar and metallic surfaces like those ofa vehicle or a guardrail. Step 114 should have already excludedguardrails, so step 117 can be a good indicator of a vehicle when strongamplitude reflections are present. Thus, if amplitude or averageamplitude are below the amplitude threshold, then class type is set toBarrier in step 115. In a further embodiment, when determining theamplitude, any amplitude contribution from the detection point havingthe strongest return may preferably be excluded. The discriminatingeffect of amplitude is increased when strong specular signals areavoided.

[0069] If a strong amplitude is found in step 117, then furtherdiscriminating tests may be performed in step 118. Thus, a change in therange of the nearest detection point, ΔNear, is compared to a respectivethreshold and if greater than the threshold, then the class type is setto Barrier in step 115. A stability Y_(stab) of a particular Y value(e.g., Y_(max) or Y_(min)) between sample times is compared to astability threshold, and if greater than the threshold, then the classtype is set to Barrier in step 115. If both ΔNear and Y_(stab) are belowtheir respective thresholds, then the class type is set to Vehicle instep 120.

[0070] If location type is not On-center in step 113, then a check ismade in step 121 to determine whether the location type stored in therecord is Rear or Front. If so, then a check is made in step 122 todetermine whether the track type is unknown. If unknown, then the classtype retains its previous value in step 111 (i.e., if track type is notknown for the object during the current sample time then a stationaryobject cannot be distinguished). If track type is known, then step 123checks whether the track type is Through. If yes, then the class type isset to Pole in step 124. If track type is not Through, then furtherdiscriminating tests may be performed in step 125. Thus, size stabilitySize_(stab) is compared to a respective size stability threshold and ifgreater than the threshold, then the class type is set to Clutter instep 126. Stability Y_(stab) of a particular Y value (e.g., Y_(max) orY_(min)) between sample times is compared to a Y-stability threshold,and if greater than the threshold, then the class type is set to Clutterin step 126. If both Size_(stab) and Y_(stab) are below their respectivethresholds, then the class type is set to Vehicle in step 120.

[0071] If location type is not Front or Rear in step 121, then a checkis made in step 127 to determine whether the location type is Spans. Ifnot, then class type is set to its previous value in step 111.Otherwise, a check is made in step 128 to compare size stabilitySize_(stab) to the respective stability threshold. If less than thethreshold then the class type is set to Vehicle in step 120. Otherwise,the class type is set to Clutter in step 126.

[0072] The alert process routine for determining whether or not toinitiate an alert to a driver based on the track type and/or the classtype is shown in FIGS. 15a and 15 b. As used in FIG. 15, a logicvariable named Alert has a value of Enabled when an object is presentwithin the zone of interest and a warning should potentially begenerated and otherwise has a value of Disabled. A logic variable namedFiltered Alert filters out instances when a stationary object isdetected and, thus, has a value of Enabled only if a detected object isdetermined to be a vehicle (e.g., in response to entry type, track type,and/or class type). Furthermore, FIGS. 15a and 15 b provide a movingwindow of class types within a respective observation period such that adecision to call an object a vehicle depends on a percentage of totalclassifications as having indicated a vehicle within the observationperiod.

[0073] The number of consecutive hits is compared with the number ofrequired hits in step 130. If ConsecHits is not greater than or equal toReqHits, then consecutive misses is compared with required misses instep 131. If ConsecMisses is greater than or equal to ReqMisses(indicating that any object that may have been present in the past hasmoved away), then Alert is set to Disabled and all type values arecleared in step 132. A logic variable LatchedClass is set to Unknown instep 133 and Filtered Alert is Disabled in step 134. LatchedClass isused in the preferred method to represent a decision that an object isin fact a vehicle, i.e., corresponding to the current observation periodincluding a selected plurality of sample times and the correspondingindividual class types.

[0074] If ConsecMisses is not greater than or equal to ReqMisses in step131, then Alert is set to its previous value in step 136. A check ismade in step 137 to determine whether the previous Filtered Alert isEnabled. If not, then LatchedClass is set to unknown in step 133.Otherwise, vehicle speed is compared with a speed threshold in step 140.

[0075] Returning to step 130, if ConsecHits is greater than or equal toReqHits, then an object is present and the value of Alert is set toEnabled in step 138. Then, vehicle speed is compared with a speedthreshold in step 140.

[0076] In the embodiment shown in FIG. 15, a driver warning is notalways initiated whenever an object is detected in the zone of interestand the host vehicle is not in motion (as opposed to the host statuslevel of FIG. 6), although FIG. 15 can be easily modified to includethat function. Instead, vehicle speed is used in the illustratedembodiment to suspend decision making while the host vehicle is stopped.Thus, if vehicle speed is not greater than or equal to a speedthreshold, then a check is made to determine whether the previous valueof Filtered Alert was Enabled and the alert routine is exited in amanner which makes no changes to any logical variables. Thus, ifFiltered Alert was previously Disabled, then the routine is exited viasteps 133 and 134; otherwise it is exited via steps 148 and 149.

[0077] If vehicle speed is greater than or equal to the speed thresholdin step 140, then a check is made in step 142 to determine the previousvalue of Filtered Alert. If it was Disabled (i.e., a decision has notyet been made to latch an object as a vehicle), then a vehicle percent(Vehicle %) is calculated in step 143. As used herein, Vehicle % meansthe percentage of times that a class type of Vehicle was detected withina selected number of sample times. The higher the Vehicle %, the higherthe confidence that an object in the zone is really a vehicle. Adecision to latch the object class as a vehicle is made by comparing theVehicle % with a threshold. A different threshold is used depending uponthe selected length of the observation period or upon the current valueof LatchedClass.

[0078] For instance, a decision about whether or not to initiate analert/warning to the driver should be made quickly when an object entersthe zone from the side or rear, but more time can be taken to make adetermination when the object enters from the front. Thus, in step 144,a check is made to determine whether the entry type for the object isside or rear. If yes (meaning that quick recognition of the presence ofa vehicle is needed and that a higher number of false positives can betolerated), then a Length (e.g., the number of samples included in theobservation period and in the Vehicle % calculation) is compared with apredetermined threshold named ShortDelaySamples (e.g., about 5 sampleperiods). If Length is less than or equal to ShortDelaySamples, then aFactor is set to a ShortDelayFactor in step 146. ShortDelayFactor mayhave a value which is liberal in deciding that an object is a vehicle(e.g., in the range of about 40% to about 60%). Vehicle % is compared tothe Factor in step 147.

[0079] If Vehicle % is less than the factor in step 147, thenLatchedClass is set to unknown in step 133 and Filtered Alert is set toDisabled in step 134. If Vehicle % is greater than or equal to thefactor in step 147, then LatchedClass is set to Vehicle in step 148 andFiltered Alert is set to Enabled in step 149.

[0080] If entry type is not side or rear in step 144 (i.e., the objectentered the front region and there is greater time to make a decision),then a check is made in step 150 to determine whether Length has reacheda predetermined number of samples LongDelaySamples (e.g., about 30samples). If yes, then a check is made in step 151 to ensure that Lengthhas not exceeded an especially large number of samples SetEvalSamples.If not exceeded, then Factor is set to a LongDelayFactor in step 152 andthe Vehicle % is compared with the LongDelayFactor in step 147.LongDelayFactor can be a more conservative value (e.g., in the range ofabout 60% to about 80%)

[0081] If Length is less than LongDelaySamples in step 150 or is greaterthan SetEvalSamples in step 151, then a return is made to steps 133 and134 via point B so that no changes are made to the logical variablesLatchedClass or Filtered Alert.

[0082] When step 142 determines that the previous value of FilteredAlert is Enabled, then Vehicle % is calculated in step 153. In thiscase, a decision has already been made to latch a decision that theobject is a vehicle. That decision can be continuously reviewed butshould not be reversed unless a substantial number of individual samplesfail to classify the object as a vehicle. A check is made in step 154 todetermine whether Length is greater than or equal to a predeterminednumber of samples ResetSamples. Once enough samples are available forconsideration, Factor is set to a ResetFactor in step 155. For example,ResetFactor may be set at 33% so that over two-thirds of class typeswould have to be other than Vehicle before a LatchedClass equal toVehicle would be changed to unknown.

[0083] Further embodiments of the present invention could use inputsfrom a steering wheel sensor to identify instances where a stationaryobject could enter the detection zone at other than the front regionbecause of turning a tight corner.

[0084]FIG. 16 shows a system block diagram including a sensor 160, suchas a radar remote sensor including a lens, antenna, and transceiver,coupled to a sensor data processor 161. Raw sensor data from sensor 160is processed by processor 161 to determine all detected scattererswithin the sensor field-of-view and preferably to create a set ofdetection points including range, range rate, beam position, returnsignal strength, and time stamp information for each detection point.This information is provided to a tracking processor 162 and/or anassessment processor 163 that determine at least a location type foreach set of detection points and use the location type with otherinformation (such as track type and class type) to assess whether toinitiate an alert mechanism 164 which may include visual or audibleannunciators of a warning (e.g., a warning light on a dashboard or awarning buzzer). Assessment information can also be provided to arestraint system 165 to facilitate pre-crash actions such as seatbeltpre-tensioning or airbag deployment.

What is claimed is:
 1. A method for controlling an object-presence alertin a vehicular side-object detection system in response to a remotesensor for sensing objects in a predetermined zone of interest alongside a vehicle, said zone of interest including a front region and arear region, said remote sensor providing sensor data to generate a setof localized detection points, said method comprising the steps of: whendetection points are sensed in said zone of interest, then collecting aplurality of respective sets of detection points at successive sampletimes; for each of said sets of detection points, determining a trackingtype of said object within said zone of interest in comparison to aspeed of said vehicle and classifying said object as either a movingvehicle or a stationary object in response to said tracking type and inresponse to locations of said detection points in said zone of interest;if said object first appeared in other than said front region, thenselecting a short observation period including a first predeterminednumber of sets of detection points and otherwise selecting a longdetection period including a second predetermined number of sets ofdetection points longer than said first predetermined number; andcomparing a number of times that said object is classified as a movingvehicle within said selected observation period to a predeterminedpercentage threshold and initiating said alert if classified as a movingvehicle for greater than said predetermined percentage threshold.
 2. Themethod of claim 1 wherein an initiated alert continues until detectionpoints cease being generated for said zone of interest.
 3. The method ofclaim 1 wherein said step of classifying said object as either a movingvehicle of a persistent stationary object is repeated for subsequentobservation periods and wherein an initiated alert is canceled if asubsequent number of times that said object is classified as a movingvehicle is less than a predetermined percentage threshold.
 4. The methodof claim 1 wherein said predetermined percentage threshold comprises afirst value when said short observation period is selected and comprisesa second value when said long observation period is selected, whereinsaid first value is less than said second value.
 5. The method of claim4 wherein said predetermined percentage threshold comprises a thirdvalue when said alert is initiated, wherein said third value is lessthan said first value.
 6. The method of claim 1 further comprising,prior to said foregoing steps, the step of: comparing a speed of saidvehicle with a speed threshold and initiating said alert if detectionpoints are generated for an object in said zone of interest and saidspeed of said vehicle is less than said speed threshold.
 7. The methodof claim 1 further comprising the step of: if said object first appearedin other than said front region, then initiating said alert.
 8. Themethod of claim 1 wherein a border between said front region and saidrear region is adjusted in response to speed of said vehicle.
 9. Amethod for controlling an object-presence alert in a vehicularside-object detection system in response to a remote sensor for sensingobjects in a predetermined zone of interest along side a vehicle, saidzone of interest including a front region and a rear region, said remotesensor providing sensor data to generate a set of localized detectionpoints, said method comprising the steps of: when detection points aregenerated for an object in said zone of interest, then determining aregion where said object first appeared in said zone of interest; ifsaid object first appeared in said front region, then tracking motion ofsaid object within said zone of interest in comparison to a speed ofsaid vehicle; foregoing said alert if said tracked motion substantiallycorresponds to a stationary object; if said tracked motion does notsubstantially correspond to a stationary object then classifying saidobject as either a moving vehicle or a persistent stationary object inresponse to locations of said detection points in said zone of interest;and initiating said alert if classified as said moving vehicle,otherwise foregoing said alert.
 10. A method for controlling anobject-presence alert in a vehicular side-object detection system inresponse to a remote sensor for sensing objects in a predetermined zoneof interest along side a vehicle, said zone of interest including afront region, a side region, and a rear region, said remote sensorproviding sensor data to generate a set of localized detection points,said method comprising the steps of: collecting a set of detectionpoints when an object enters said zone of interest; identifying which ofsaid front, side, or rear regions said object first appeared in; and ifsaid object first appeared in other than said front region, theninitiating said alert, otherwise foregoing said alert with respect tosaid object.